Paramedic Intubation during a Pandemic: Where are the Consensus Guidelines?
Bibliographic record
Abstract
There is no denying that paramedic-led intubation is a contentious issue in out-of-hospital care. Guidelines for the management of COVID-19 are developed with both patient-centred care as well as provider safety in mind, with intubation the preferred airway management strategy in patients suspected to have contracted COVID-19 requiring airway protection or invasive ventilation. However, this has re-ignited a debate which began during the Severe Acute Respiratory Syndrome (SARS) outbreak in the early 2000s around whether the benefit of paramedic-led intubation outweighs the risks to providers during a pandemic. The aim of this commentary is to revisit the evidence around paramedic-led intubation and provide a perspective on paramedic-led intubation during the COVID-19 pandemic. It is hoped this will stimulate further discussion around the benefits and risks of paramedic intubation in the setting of a pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.234 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.023 | 0.026 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".